Technical Content

The attenuation of surface related multiples is typically one of the most challenging steps in the processing of shallow water marine projects. Least-squares wave-equation deconvolution imaging is a powerful tool to address this challenge, but images derived from a deep target level may produce ...

A high-resolution seismic image is of great importance to exploration and production in many ways, such as bypassing drilling hazards and identifying compartmentalized reservoirs. To achieve seismic resolution as high as possible, the conventional seismic imaging process takes more of a linear approach to ...

4D time-lapse seismic imaging is typically performed using the same velocity model to migrate the baseline and monitor data. However, in complex cases where one producing reservoir sits above another, significant changes in the properties of the overlying reservoir can result in a 4D ...

Stratal geometries, reservoir and source facies are different in true lakes, in lakes with restricted access to the global ocean, and in “lakes” continuously connected to the global ocean but capped by large quantities of freshwater. We illustrate the importance for exploration and development ...

Small-scale heterogeneities create distortions in the wavefield that are usually resolved by Full Waveform Inversion (FWI). When FWI fails (for lack of diving waves or low frequencies), recent works promote the use of targeted stochastic approaches maximizing the stack power. We instead revisit here ...

The quality of time-lapse analysis depends highly on the repeatability of the acquisition. However, in practice, it is almost impossible to perfectly mimic a base survey due to environmental conditions and inaccurate measurements. Lack of repeatability often results in 4D noise, which may compromise ...

Convolutional based deep neural networks can be used in addition to existing workflows, to improve turnaround or as a ‘guide’ for further processing. Whilst a lot of effort has been made to try to improve the DNN architecture for processing tasks or to understand ...

Learning how to best mimic seismic processing algorithms or workflows with deep learning (DL) has become a very active field of research. However, seismic processing own particularities may necessitate adaptations of current DL methods. In this paper, we explain and illustrate how the different ...

Depth imaging of converted-wave (P-to-S) ocean-bottom seismic (OBS) data requires a depth model for both the P- and S-wave velocities. Building the S-wave velocity model is very challenging: conventional techniques include PP and PS image registration, or joint PP and PS tomography. These approaches ...